\begin{table}
\centering\centering
\caption{Black candidate profiles and partisan considerations.}
\centering
\fontsize{9}{11}\selectfont
\begin{threeparttable}
\begin{tabular}[t]{lc>{\centering\arraybackslash}p{2cm}>{\centering\arraybackslash}p{2cm}>{\centering\arraybackslash}p{2cm}c}
\toprule
\multicolumn{1}{c}{ } & \multicolumn{2}{c}{DV: Black candidate selected} & \multicolumn{3}{c}{DV: This candidate...} \\
\cmidrule(l{3pt}r{3pt}){2-3} \cmidrule(l{3pt}r{3pt}){4-6}
\multicolumn{3}{c}{ } & \multicolumn{1}{c}{\makecell[c]{has a good chance\\of winning the\\general election}} & \multicolumn{1}{c}{\makecell[c]{can appeal\\to swing\\voters}} & \multicolumn{1}{c}{\makecell[c]{can appeal\\to Democratic\\base}} \\
\cmidrule(l{3pt}r{3pt}){4-4} \cmidrule(l{3pt}r{3pt}){5-5} \cmidrule(l{3pt}r{3pt}){6-6}
  & &nbsp;(1) & &nbsp;&nbsp;(2) & &nbsp;&nbsp;(3) & &nbsp;&nbsp;(4) & &nbsp;&nbsp;(5)\\
\midrule
Moderate Democrat & 0.100 & 0.071 &  &  & \\
 & (0.063) & (0.063) &  &  & \\
Strong Democrat & 0.098+ & 0.059 &  &  & \\
 & (0.059) & (0.059) &  &  & \\
Racial resentment &  & −0.279** &  &  & \\
 &  & (0.087) &  &  & \\
Black candidate &  &  & −0.023*** & −0.006 & 0.024***\\
 &  &  & (0.004) & (0.004) & (0.004)\\
Intercept & 0.496*** & 0.626*** & 0.519*** & 0.490*** & 0.567***\\
 & (0.048) & (0.062) & (0.003) & (0.003) & (0.003)\\
Num.Obs. & 469 & 469 & 8928 & 8932 & 8926\\
R2 & 0.007 & 0.029 & 0.004 & 0.000 & 0.004\\
\bottomrule
\multicolumn{6}{l}{\rule{0pt}{1em}+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001}\\
\end{tabular}
\begin{tablenotes}
\item \textit{Note: } 
\item This table presents the results of linear regression models. In Columns (1)-(2), the dependent variable is selecting a Black candidate profile and the explanatory variable is the strength of participants' Democratic partisanship. Data are from Lucid Study 1. In Columns (3)-(5), the dependent variable is ratings of the candidate and the explanatory variable is the race of the candidate. White is the reference category. Data are from Lucid Studies 1 and 2. Data in all models are weighted for demographic representativeness by gender, region, and age group.
\end{tablenotes}
\end{threeparttable}
\end{table}
